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Paper Citation Record · LEDGER

A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2401.16402.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2401.16402 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:57:04.556285Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

9
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3c02bd78-f604-42d4-b6e8-301cbf2e96cd · inbound

ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift cites this paper.

ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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unresolved
no resolver link, observed 2026-08-12T13:39:38.543325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:39:38.543325Z digest=sha256:cfa36351c2429ea13686a7a72dcd915db6a199857e2c8b4bde62f484503eaed0

Observation 25100388-7f90-4add-bbb5-f23867fb6122 · inbound

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties cites this paper.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 8

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unresolved
no resolver link, observed 2026-08-11T12:07:51.236255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:07:51.236255Z digest=sha256:448161ebce495b6a0e0b9c4becff0681caecb551eccf49069c76854d7d5e4135

Observation b1e9870d-f13c-4876-ae3c-b5949295a663 · inbound

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection? cites this paper.

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection? A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

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unresolved
no resolver link, observed 2026-08-10T14:03:30.950201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:03:30.950201Z digest=sha256:7855ff7b519de013c72d43280d979d04a11a908c274344c8e26fe0548140bbea

Observation 13feb1b7-5809-4631-8256-723e7e6aea04 · inbound

3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly cites this paper.

3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 5

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unresolved
no resolver link, observed 2026-08-08T18:08:02.581927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:08:02.581927Z digest=sha256:8fd0fadef95019b324b40a2614636756d75048a22967670e3f0201911fbb26c4

Observation 52238573-fb9e-4ff6-8686-4a4b1561f796 · inbound

Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection cites this paper.

Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 6

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unresolved
no resolver link, observed 2026-08-16T11:57:04.556285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:57:04.556285Z digest=sha256:cb73770e3fc191198557103e968d9a19448d4feba528e1261bded4a6896c3ac5

Observation bfc705f3-9a44-40b2-a0f7-21b20f850b2c · inbound

RoBiS: Robust Binary Segmentation for High-Resolution Industrial Images cites this paper.

RoBiS: Robust Binary Segmentation for High-Resolution Industrial Images A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T13:43:19.564441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:43:19.564441Z digest=sha256:870c858de60a7468a66c5212a46d0eb197c93ab65978a283845e3e08d1c39b3e

Observation 0d8d4d6b-ef16-4a97-8ae1-00b0847a108b · inbound

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning cites this paper.

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T11:03:10.179143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:10.179143Z digest=sha256:f281e0e0e13a8ea498187637f93a7004bc224fc7e2724c279124a417b63be74c

Observation 6e4df65f-c3a3-4497-90c1-a70de2bb8739 · inbound

IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain cites this paper.

IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 12

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no resolver link, observed 2026-08-07T04:28:33.889507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:28:33.889507Z digest=sha256:711d5b32cbabfe9236923d2cbf830df227cf441cd9a114c5c8eeb77c27bd92f5

Observation fb3c09f8-c92a-4682-9b20-820db08f938d · inbound

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology cites this paper.

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 7

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no resolver link, observed 2026-08-06T23:10:07.273869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:07.273869Z digest=sha256:0727c42dfdeb1b28b26da1f76b876f664dafbc13eda95ad033a19ccf74cd4cc4

Observation b1e08200-9070-44a0-9221-a2fc00ca7fe4 · inbound

Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection cites this paper.

Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 6

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unresolved
no resolver link, observed 2026-08-06T17:27:14.370852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:27:14.370852Z digest=sha256:3e783fad5d98811960881aa989c61482c433243645de78fc3bebd0d8e0ebb064

Observation 0586d6c5-16c4-4d0e-b566-d98a2546d706 · inbound

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects cites this paper.

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

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unresolved
no resolver link, observed 2026-08-06T17:21:37.814140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:21:37.814140Z digest=sha256:19fd43477099368582771171213d59f8eefcc486975ecf912929b59912170578

Observation 451ac339-7fed-44e0-b369-95bb97edd32f · inbound

Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts cites this paper.

Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 8

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unresolved
no resolver link, observed 2026-08-06T15:06:24.391064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:06:24.391064Z digest=sha256:791b03094a7ed78f1e23484707ee42d1dc9b3f2a9278e8451a751858596c7532

Observation 850c0368-daaf-4000-8600-65c757fd7985 · inbound

MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection cites this paper.

MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 18

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unresolved
no resolver link, observed 2026-08-15T15:59:52.510832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:59:52.510832Z digest=sha256:d9f1313d54623997c70de3672d5247d4445696130db6f3ac17cb2257769048db

Observation 4031733d-72e8-47bf-8187-2146473587c1 · inbound

Normality Calibration in Semi-supervised Graph Anomaly Detection cites this paper.

Normality Calibration in Semi-supervised Graph Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 1

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unresolved
no resolver link, observed 2026-08-04T12:48:07.552118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:48:07.552118Z digest=sha256:1d140049c4cb829bdbb017bcfc99592a13fbf94846a793324043791dd267035a

Observation 7c4ae927-032b-43a3-b996-0ed92a823508 · inbound

SGANet: Semantic and Geometric Alignment for Multimodal Multi-view Anomaly Detection cites this paper.

SGANet: Semantic and Geometric Alignment for Multimodal Multi-view Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:05:48.336594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T20:16:06.916465Z digest=sha256:99a91d74732c9eeacad7e706d5af855871f88eb3ce740997cdd0d514796f67c8

Observation 0ba0a0f9-19aa-4d8c-845e-e5684879f3b7 · inbound

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis cites this paper.

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 2

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verified exact
arxiv_id, observed 2026-05-11T00:35:49.404243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T18:27:36.529298Z digest=sha256:985d58cdff60576d6cba3b2b51eb5ea2e057626d72bb18dca8b700f7af48ec4d

Observation 424e1e87-4438-42b0-a255-3b4132df0fb8 · inbound

Beyond Normal References: Discriminative Few-Shot Anomaly Detection cites this paper.

Beyond Normal References: Discriminative Few-Shot Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 2

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verified exact
arxiv_id, observed 2026-05-25T04:55:23.664104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-25T04:52:07.114651Z digest=sha256:3f1d1fdc42e1a7387cdb71dab50e278254a3c8aa04197c8a2cf973843bfd86f4

Observation 119bd49d-f4b8-4254-b0a9-56362bd330ec · inbound

Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces cites this paper.

Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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verified exact
arxiv_id, observed 2026-06-30T13:54:44.040833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T13:48:39.954133Z digest=sha256:451f92fdb4d280ae30d1322018629d7da983d0b6fb74a4dcf57536a816f1f851

Observation 0f7edb27-980b-461c-bf01-b4aa0f51d615 · inbound

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection cites this paper.

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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verified exact
arxiv_id, observed 2026-06-29T08:13:14.940540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-29T08:10:15.306343Z digest=sha256:811cad000404b1309a5361c9b68184811167dd528d2b51204ab4d3b5f1dae894

Observation 536d2f97-8c91-4749-9a1a-943838807657 · inbound

HiMatch-AD: DINOv3-driven Hierarchical Matching for Training-free Medical Anomaly Detection cites this paper.

HiMatch-AD: DINOv3-driven Hierarchical Matching for Training-free Medical Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 7

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verified exact
arxiv_id, observed 2026-07-04T08:39:42.031321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T11:16:57.088304Z digest=sha256:e1ea5129e1474ac69dfbc1864db6b497651373cc4f054e9ac20732e374bdf75a

Observation cd9c8230-8b66-4159-894f-d9a31908934f · inbound

MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection cites this paper.

MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 16

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metadata mismatch
arxiv_id, observed 2026-07-04T09:49:44.646264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T09:26:51.456652Z digest=sha256:3f5cc066f6e2c85584998b83f2ae5bb4635a454e544d77bbe771f61e45426ecf

Observation 4d9bc430-1345-4a97-8376-0cedb2278b18 · inbound

CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection cites this paper.

CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 7

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verified exact
arxiv_id, observed 2026-07-04T19:50:10.591635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-25T20:59:46.355482Z digest=sha256:946909411ac5cdd61844b7037797c1c592629f322c1d882827a8f6eac5ceb00c

Observation 25a0d44a-ee7b-4dd9-ad76-66f1b891629d · inbound

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation cites this paper.

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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metadata mismatch
arxiv_id, observed 2026-07-01T17:15:50.964359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-29T04:05:22.253489Z digest=sha256:1ee3fc1c6ee83e5e9256be346cdd4b140466a84598fd714ffc3ab6a2a5e6bae4

Observation ad0b0165-bd65-4a8d-8b50-dffdbf8e57d2 · inbound

Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection cites this paper.

Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

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verified exact
arxiv_id, observed 2026-06-30T07:54:21.172788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T07:53:44.196356Z digest=sha256:8203d07c9ac426cc298cfd89eeaad657e7ab57e457d6323b7f49492783d2bae5

Observation 4297816f-9c2f-49b2-bbc4-68473cd4ae7e · inbound

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors cites this paper.

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 5

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verified exact
arxiv_id, observed 2026-06-30T07:54:21.686229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T07:54:02.833347Z digest=sha256:9afda3fcda9438c912338f7191d3266beef153eb59a3910db6822a5d92bee20c